CN107966444A - 基于模板的纺织品瑕疵检测方法 - Google Patents
基于模板的纺织品瑕疵检测方法 Download PDFInfo
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- CN107966444A CN107966444A CN201710946432.5A CN201710946432A CN107966444A CN 107966444 A CN107966444 A CN 107966444A CN 201710946432 A CN201710946432 A CN 201710946432A CN 107966444 A CN107966444 A CN 107966444A
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- 239000004753 textile Substances 0.000 title claims abstract description 61
- 238000001514 detection method Methods 0.000 title claims abstract description 30
- 230000000737 periodic effect Effects 0.000 claims abstract description 7
- 238000000034 method Methods 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 7
- 239000004744 fabric Substances 0.000 claims 1
- 238000009987 spinning Methods 0.000 claims 1
- 238000009941 weaving Methods 0.000 claims 1
- 238000007689 inspection Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 10
- 230000007547 defect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 238000011426 transformation method Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8883—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges involving the calculation of gauges, generating models
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Image Analysis (AREA)
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CN201710946432.5A CN107966444B (zh) | 2017-10-12 | 2017-10-12 | 基于模板的纺织品瑕疵检测方法 |
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CN107966444A true CN107966444A (zh) | 2018-04-27 |
CN107966444B CN107966444B (zh) | 2020-03-27 |
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Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109472769A (zh) * | 2018-09-26 | 2019-03-15 | 成都数之联科技有限公司 | 一种不良图像缺陷检测方法和*** |
CN110838111A (zh) * | 2019-11-08 | 2020-02-25 | 深圳市深视创新科技有限公司 | 柔性电路板的自适应缺陷检测方法 |
CN110852989A (zh) * | 2019-09-30 | 2020-02-28 | 广州利科科技有限公司 | 瓷砖拍照图片的质量瑕疵检测 |
CN111028289A (zh) * | 2019-11-20 | 2020-04-17 | 国网浙江省电力有限公司电力科学研究院 | 基于模板匹配的变电站内设备异物定位方法 |
CN111784691A (zh) * | 2020-07-27 | 2020-10-16 | 泉州迈斯特新材料科技有限公司 | 一种纺织品瑕疵检测方法 |
CN111915549A (zh) * | 2019-05-09 | 2020-11-10 | 富泰华工业(深圳)有限公司 | 瑕疵检测方法、电子装置及计算机可读存储介质 |
CN112465743A (zh) * | 2020-10-20 | 2021-03-09 | 天津大学 | 一种周期性结构质量检测方法 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2004212392A (ja) * | 2002-12-17 | 2004-07-29 | Okayama Prefecture | 表面検査方法 |
CN101866427A (zh) * | 2010-07-06 | 2010-10-20 | 西安电子科技大学 | 织物瑕疵检测与分类方法 |
CN103402042A (zh) * | 2013-07-31 | 2013-11-20 | 浙江大学 | 基于分块式误差扩散的半色调图像生成方法 |
CN103604809A (zh) * | 2013-10-22 | 2014-02-26 | 江南大学 | 一种图案布匹瑕疵在线视觉检测方法 |
CN106296689A (zh) * | 2016-08-10 | 2017-01-04 | 常州信息职业技术学院 | 瑕疵检测方法、***及装置 |
-
2017
- 2017-10-12 CN CN201710946432.5A patent/CN107966444B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2004212392A (ja) * | 2002-12-17 | 2004-07-29 | Okayama Prefecture | 表面検査方法 |
CN101866427A (zh) * | 2010-07-06 | 2010-10-20 | 西安电子科技大学 | 织物瑕疵检测与分类方法 |
CN103402042A (zh) * | 2013-07-31 | 2013-11-20 | 浙江大学 | 基于分块式误差扩散的半色调图像生成方法 |
CN103604809A (zh) * | 2013-10-22 | 2014-02-26 | 江南大学 | 一种图案布匹瑕疵在线视觉检测方法 |
CN106296689A (zh) * | 2016-08-10 | 2017-01-04 | 常州信息职业技术学院 | 瑕疵检测方法、***及装置 |
Non-Patent Citations (3)
Title |
---|
DORIAN SCHNEIDER ET AL.: "A traverse inspection system for high precision visual on-loom fabric defect detection", 《MACHINE VISION AND APPLICATIONS》 * |
吴黎明等: "重复图案晶片自动检测新方法", 《光学精密工程》 * |
梁久祯等: "基于相似关系的纺织品瑕疵检测方法", 《模式识别与人工智能》 * |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109472769A (zh) * | 2018-09-26 | 2019-03-15 | 成都数之联科技有限公司 | 一种不良图像缺陷检测方法和*** |
CN111915549A (zh) * | 2019-05-09 | 2020-11-10 | 富泰华工业(深圳)有限公司 | 瑕疵检测方法、电子装置及计算机可读存储介质 |
CN110852989A (zh) * | 2019-09-30 | 2020-02-28 | 广州利科科技有限公司 | 瓷砖拍照图片的质量瑕疵检测 |
CN110852989B (zh) * | 2019-09-30 | 2022-05-13 | 广州利科科技有限公司 | 瓷砖拍照图片的质量瑕疵检测 |
CN110838111A (zh) * | 2019-11-08 | 2020-02-25 | 深圳市深视创新科技有限公司 | 柔性电路板的自适应缺陷检测方法 |
CN111028289A (zh) * | 2019-11-20 | 2020-04-17 | 国网浙江省电力有限公司电力科学研究院 | 基于模板匹配的变电站内设备异物定位方法 |
CN111028289B (zh) * | 2019-11-20 | 2022-05-17 | 国网浙江省电力有限公司电力科学研究院 | 基于模板匹配的变电站内设备异物定位方法 |
CN111784691A (zh) * | 2020-07-27 | 2020-10-16 | 泉州迈斯特新材料科技有限公司 | 一种纺织品瑕疵检测方法 |
CN112465743A (zh) * | 2020-10-20 | 2021-03-09 | 天津大学 | 一种周期性结构质量检测方法 |
CN112465743B (zh) * | 2020-10-20 | 2022-04-22 | 天津大学 | 一种周期性结构质量检测方法 |
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